Neural network approximations for nonlinear interactions in wind wave spectra: direct mapping for wind seas in deep water

The potential of Neural Networks (NN) to provide accurate estimates of nonlinear interactions for wind wave spectra by means of direct mapping is considered. Expanding on a previously reported feasibility study, an Empirical Orthogonal Functions (EOF) based NN for single peaked spectra is shown to b...

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Bibliographic Details
Published in:Ocean modelling (Oxford) 2005, Vol.8 (3), p.253-278
Main Authors: Tolman, Hendrik L., Krasnopolsky, Vladimir M., Chalikov, Dmitry V.
Format: Article
Language:English
Subjects:
Empirical orthogonal functions
Marine
Neural networks
Nonlinear interactions
Numerical modeling
Wave model physics
Wind waves
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Summary:The potential of Neural Networks (NN) to provide accurate estimates of nonlinear interactions for wind wave spectra by means of direct mapping is considered. Expanding on a previously reported feasibility study, an Empirical Orthogonal Functions (EOF) based NN for single peaked spectra is shown to be much more accurate than the well known Discrete Interaction Approximation (DIA), at the expense of a moderate increase of computational costs. This Neural Network Interaction Approximation (NNIA) gives reasonable results for modeled wave spectra, but is not yet capable of providing acceptable model integrations. Methods to expand the NNIA to be suitable for model integration are discussed.
ISSN:1463-5003
1463-5011
DOI:10.1016/j.ocemod.2003.12.008